Use this URL to cite or link to this record in EThOS:
Title: Novel particle sizing techniques
Author: Chen, Rui
Awarding Body: University of Nottingham
Current Institution: University of Nottingham
Date of Award: 2013
Availability of Full Text:
Access through EThOS:
Access through Institution:
Two novel approaches to particle size measurement are investigated; these are designated as Particle Movement Displacement Distribution (PMDD) method and Separated Multiple Image Technique (SMIT). An advantage of these methods compared with the established particle sizing methods of Static Light Scattering (SLS) and Dynamic Light Scattering (DLS) is that PMDD and SMIT do not suffer from the intensity weighting problem that affects SLS and DLS. The performance of the PMDD method is examined through computer simulations and through analysis of pre-existing experimental data. The SMIT method is investigated through computer simulations and through the construction and use of an optical system. The ability of both methods was measured through the assessment of an ‘area error’ measure which gives an estimate of the accuracy of a recovered particle size distribution. This area error measure varies between 0 and 2; with 0 corresponding to a perfectly recovered distribution. Typically a good inversion of DLS data can achieve an area-error value of 0.32 to 0.34 and this figure (along with the recovered mean particle size and standard deviation of the distribution) was used to judge quantitatively the success of the methods. The PMDD method measures the centre of individual particles in each image. A vector histogram is formed based on the connection between the centres in the first image and the centres in the next image. This vector histogram contains information about the particle size distribution. A maximum likelihood data inversion procedure is used to yield a particle size distribution from this data. The SMIT method is similar to the Static Light Scattering (SLS) method, but it combines angular dependent intensity method and individual visualisation method together to recover individual particle sizes without an intensity weighting. A multi-aperture mask and wedge prisms are utilised in this method to capture particle images formed from light scattered into a number of selected directions. A look-up table is then used to recover the individual particle sizes, which are then formed into a histogram. For the PMDD method, computer simulation results established the optimum values for parameters such as the time interval between frames, the exposure time and the particle concentration and also investigated the effects of different noise sources. For mono-modal size distributions, the PMDD method was shown through computer simulation to be capable of recovering a particle size distribution with an area error of around 0.27 which compares well with the typical DLS result. PMDD results were also recovered from mono-modal experimental data with mean particle sizes close to the manufacturers quoted particle mean size. However, recovery of bi-modal distributions was found to be not so successful; for bi-modal distributions, the recovered distributions generally had only a single peak, which, of course gives a very poor area-error figure. This result compares poorly with the particle tracking method ‘Nano Particle Tracking Analysis’ which is able to recover bi-modal distributions. For this reason further research was concentrated on an image intensity method (SMIT). For the SMIT method, computer simulation results established the optimum values for parameters such as the particle concentration and also investigated the effects of different noise sources and of aberrations in the optical system. The SMIT method was shown through computer simulation to be capable of recovering particle size distributions for both mono-modal and bi-modal distributions. The area error values obtained were in the range 0.24 to 0.45, and most of the results are good compared to the DLS value. The major problem with the SMIT method was found to be the presence of a small number of recovered particle radii much larger (or smaller) than the true sizes. These errors were attributed to ambiguities in the look-up table system used to convert the relative intensity data values into particle sizes. Two potential methods to reduce the influence of these ambiguities were investigated. These were, firstly by combining Brownian motion movement data from tracking individual particles over a few frames of data, and secondly by combining an estimate of the total scattered intensity from a particle with the normal SMIT data to constrain the look-up procedure. In computer simulations both approaches gave some improvement but the use of the total scattered intensity method gave the better results. In a computer simulation this method managed to improve the area-error from 0.37 for SMIT alone to 0.25 for SMIT combined with this extra information. Based on the success of these computer simulation results, an experimental SMIT system was constructed and tested. It was found necessary to first calibrate the optical system, to account for the different optical transmission coefficients of the different prisms/optical paths. But using a particle sample with particles of known size to calibrate; other particle sizes were successfully recovered from the experimental data using the original SMIT data processing. A majority of the recovered particle radius were close to the manufacturers quoted particle mean radius. Attempts to implement the total intensity approach to enhance the SMIT were found not be successful due to the difficulty in measuring the small displacements in particle positions required with sufficient accuracy. A possible alternative design to overcome this problem is suggested in the future work section 7.2.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: TA Engineering (General). Civil engineering (General)